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中国农学通报 ›› 2017, Vol. 33 ›› Issue (23): 83-88.doi: 10.11924/j.issn.1000-6850.casb16100095

所属专题: 现代农业发展与乡村振兴 农业气象

• 资源 环境 生态 土壤 气象 • 上一篇    下一篇

安徽省农业气象灾害时间分布特征与灰色关联分析

吕 凯,陈 磊,高振魁,张彩丽,李继红   

  1. 安徽省农业科学院农业经济与信息研究所,安徽省农业科学院农业经济与信息研究所,安徽省农业科学院农业经济与信息研究所,安徽省农业科学院农业经济与信息研究所,安徽省农业科学院农业经济与信息研究所
  • 收稿日期:2016-10-24 修回日期:2017-07-17 接受日期:2016-11-23 出版日期:2017-08-21 发布日期:2017-08-21
  • 通讯作者: 李继红
  • 基金资助:
    安徽省农科院学科建设项目“信息计量学在安徽水稻科研态势分析中的应用”(17A1431);安徽省农业科学院安徽省农业灾害风险分析研 究科技创新团队(14C1409)。

Agro-meteorological Disasters in Anhui: Temporal Distribution Characteristics and Grey Correlation Analysis

  • Received:2016-10-24 Revised:2017-07-17 Accepted:2016-11-23 Online:2017-08-21 Published:2017-08-21

摘要: 为了探寻安徽省农业气象灾害的分布特点以及各种气象灾害对粮食生产的影响,本研究基于安徽省1992—2012年有关气象灾害数据,对4种主要气象灾害(旱灾、水灾、风雹灾、霜冻灾)的分布特征做了统计分析,并采用灰色关联分析研究其对安徽省粮食单产的影响。结果表明:从1992—2012年,安徽省气象灾害具有发生频率高、波动大的特点,但整体上呈下降趋势。旱灾和水灾是发生面积较大的气象灾害,且常常在时间上交织、空间上并存。灰色关联分析表明,4种气象灾害对粮食产量影响顺序如下:风雹灾>水灾>旱灾>霜冻灾,说明风雹灾是影响粮食产量最主要的气象灾害,其次是水灾、旱灾,霜冻灾影响较小。本研究可为安徽省防灾减灾措施的制定提供决策依据。

关键词: 邻苯二甲酸酯(PAEs), 邻苯二甲酸酯(PAEs), 蔬菜, 残留

Abstract: The paper aims to explore the distribution characteristics of agro-meteorological disasters in Anhui and their impact on grain yield. Based on the disaster-affected areas of 4 agro-meteorological disasters including drought, flood, wind-hail and frost, combining with grain yield data from 1971 to 2012, the temporal distribution of these disasters was analyzed in this paper, as well as the correlation relation between disaster-affected area and average grain yield. The results showed that agro-meteorological disasters occurred frequently and fluctuated greatly, presenting a declining trend. Drought and flood were the main agro-meteorological disasters, and they often coexist in same time and space. Gray correlation analysis indicated that the impact of agro-meteorological disasters on average grain yield appeared in the order of wind-hail>flood>drought>frost in Anhui, which revealed wind-hail was the major agro-meteorological disaster during grain production, followed by flood, drought and frost. The results can provide decision-making basis for prevention of natural disasters in the future.

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